Sustainable Education and University Students’ Well-Being in the Digital Age: A Mixed-Methods Study on Problematic Smartphone Use

Abstract

In the digital age, smartphone use among university students has become problematic, with implications for education and personal well-being. This study aimed to investigate research directions on problematic smartphone use among students, gaps in the field, and emerging research directions, along with validating the data among some Romanian students, as a preliminary perspective. The first part of the study included a bibliometric investigation using the Web of Science Core Collection database and version 1.6.20 of the VOSviewer software; 593 papers were validated for the period 2007–2025 (5 February), which allowed us to analyze author networks, citations, keywords, and collaborations. The second part of the research was based on a cross-sectional study to capture the particularities of this phenomenon among some Romanian students. Smartphone use also appears to be problematic among the Romanian surveyed students, as is the international trend; the responses of the surveyed students show the existence of compulsive behavior towards smartphone use, which suggests a self-control conflict. This comprehensive investigation allows for the prediction of trends and provides relevant information for future research, as well as serving as a basis for political and academic decisions, for sustainable digital transformation within universities and to the achievement of sustainable education.

1. Introduction

The intense and continuous development of information and communication technologies has led to the digital era, or the fourth industrial revolution (Industry 4.0), which has impacted the evolution of all spheres of human activity [1], including emotional, physical, educational, professional, social, and digital spheres, among others. Industry 4.0 is viewed as a revolutionary transformation involving intelligent machines, device interconnectivity, and decision-making based on accurate information, where the boundaries between digital, physical, and biological realities are weakened, become vague, or may even disappear [2].

At the level of higher education institutions, digitalization is an issue that involves all actors; therefore, the subject is of general interest, and concern for it is a common responsibility. Digital skills have become basic requirements in the educational and professional fields, being indispensable for the social and professional integration of individuals. Universities prepare professionals who can handle changes and challenges, finding solutions and alternatives, including the assistance of digital skills as vital skills [3]. Learning based on digital technologies is seen as an activity of personal interests and experiences; therefore, students are positioned in personal educational stages, along with personal feedback cycles, which contribute to self-improvement [4].

The transition from traditional procedures and processes to digital procedures and processes specific to the current industrial revolution was achieved with the help of specific tools, such as smart devices (PCs), and especially portable ones (tablets, smartphones, PDAs, smartwatches, body sensors, etc.), various software and platforms (ERP, Moodle, Google Workspace, etc.), digital and social networks (Google Drive, Facebook, X), automation, and various tools (virtual assistants, banking applications, VPN). Of all the above, the smartphone is the most widely used digital device that people, especially young people, use when they want to access the internet for shopping, various applications, online services, etc. Young people and students also use it for gaming, socializing, accessing educational platforms, and utilizing online libraries.

The literature in the field presents the benefits of smartphones in students’ lives, such as easy access to and sharing of teaching materials, convenient communication with other students and faculty staff, and smartphone portability [5,6,7,8]. Ref. [9] believe that universities can use students’ smartphones as educational tools; they developed a mobile application for first-year students to integrate them into the university environment by facilitating their relationships with tutors and mentors, hoping to reduce the dropout rate. Previously, Ref. [10] also developed a computer-assisted education platform based on mobile communication technology and cloud computing, which would serve as a permanent place of communication between teachers and students, ensuring an increase in the quality of the educational act.

The disadvantages are also presented, as problematic smartphone use among students has become a global issue [11]. Studies show that there is a significant link between the frequency of smartphone use and problematic use, including internet addiction or cyberloafing—in the case of students, as using the internet for personal activities rather than for study [12,13]. Ref. [14] lists accusations such as students wasting time, missing studies, avoiding exercise, watching inappropriate digital content, and being inattentive on the road or while driving.

Problematic smartphone use has been correlated with addictive behaviors. Among these addictive behaviors, some authors have addressed nomophobia or the fear of being without a mobile phone [15,16,17,18,19,20,21,22,23] which can lead to social isolation, fear of social interactions, physical, psychological, and emotional problems (headaches, tachycardia, stress, nervousness, anxiety, depression, low self-esteem). Others have studied the correlations with fear of missing out (FOMO), such as Ref. [16], who concluded that there is a moderate positive relationship between the level of nomophobia and the level of FOMO, or Ref. [24] who concluded that the level of FOMO is strongly related to distraction and disengagement from learning. The authors have created and evaluated measures of FOMO [25,26], and have linked FOMO to the need for belonging, fear of social exclusion, and addiction to social networks [27,28].

Finally, studies on smartphone use among students have been linked to physical, mental, and emotional health problems, as well as with the impact on social relationships [29,30,31,32,33,34,35,36,37,38,39], including phubbing, which occurs when a person ignores those around them in favor of their smartphone [40,41,42].

The studies mentioned above demonstrate the complexity and interdisciplinarity of the topic. We can see that the issue of smartphone use among students cannot be addressed solely within a certain field, as it inevitably intersects with others due to its complex, multidimensional nature. We also observe that the studies are influenced by the temporal context, priorities, and trends specific to the period (year) of publication, and this fact may affect the formulation of a general conclusion regarding the topic of problematic smartphone use among students.

To provide a more complete picture of the complex and multifaceted phenomenon of problematic smartphone use among students, this study integrated a methodological triangulation approach. More precisely, it combined a detailed bibliometric investigation of current research in the field with a quantitative cross-sectional study, conducted on a sample of Romanian students.

The bibliometric analysis aimed to capture the interest expressed at the international scientific level regarding the subject, to identify the main research directions, the authors and countries involved, and the emerging research directions, as well as the gaps in the field, including the inequality of the distribution of research at the international level, but also the underrepresentation of research in the Romanian context. The analysis did not specifically target only certain aspects or sub-themes of the issue but aimed to provide a comprehensive and extensive approach to the literature in the field, which allowed an integrative examination of the topic that would cover all dimensions and interdependent elements, by capturing the multidimensional aspects of the subject and contributing to obtaining relevant and well-founded conclusions. The results obtained through the bibliometric analysis led to the desire to deepen the research through a questionnaire among a sample of Romanian students, to observe whether the manifestations follow the international trend. At the same time, the results served to formulate the questionnaire by adapting for Romanian students the notions and elements found in the literature in the same thematic area.

The results obtained in the two stages of our research were triangulated, which allowed for a more complete picture of the phenomenon, a deepening of the results, and a better contextualization of them, considering the complementary approach. Thus, the analysis of secondary data showed the research directions in the field but also identified the gaps. Complementing with the collection of primary data, we were able to connect the research at the macro level with a capture of the phenomenon at the local, contextual level. Our scientific approach complements the literature in the field, but also offers an applied dimension, allowing the formulation of recommendations for university administrators and decision-makers. In addition, methodological triangulation allowed the confirmation of some research directions, while capturing some local characteristics, which can serve for future research.

The paper is structured into four sections, as follows: Section 1 serves as a theoretical preamble to the digital age, connected with the analysis of the literature in the field; Section 2 details the research methodology, as well as the data source, search strategy, and processing issues for both for the bibliometric analysis and the cross-sectional study; Section 3 analyzes the main results and discusses the findings; Section 4 highlights the contributions of the present study, which facilitated an assessment of the scientific impact of the literature in the field, the development directions, and of the challenges.

2. Materials and Methods

2.1. Methods

Large and complex amounts of scientific data involve finding and using a suitable method of analysis; this can be bibliometric analysis [43,44]. Bibliometric analyses are extremely valuable in research because they allow an assessment of scientific impact (citation analysis, identification of reference works and authors, spread of collaborations and partnerships, research fields, impact of journals, etc.), but also a forecast of trends in the field and emerging research directions, which provide valuable information for political and academic decisions, institutions, funders, and researchers. The impressive contribution of bibliometrics to recent research can be attributed to a combination of variables; thus, on the one hand, we have the development of software packages and tools such as VOSviewer, CitNetExplorer, Bibliometrix, and Publish, which are used to analyze scientific literature, citation networks, relationships between publications, authors, citations, and keywords, and on the other hand we have the establishment of important and rigorous scientific databases, such as Web of Science (WOS), Scopus, and Google Scholar, which offer generous collections of works, but also integrated analysis tools [44,45,46,47,48,49,50].

Thus, for the first part of the research, a bibliometric analysis was carried out on the topic of problematic smartphone use by students by accessing the Web of Science Core Collection database, because it allows us access to scientific articles and provides us with information about citations, collaborations between authors, institutions and countries, affiliations, research fields, etc., but it also allows us to extract data by exporting, to be used in statistical analyses. To create visual maps in our bibliometric analysis, we used VOSviewer software, version 1.6.20. It allows us to analyze author networks, citations, keywords, and collaborations, so that we can identify the main directions of the research topic, thus identifying gaps in the field as well as emerging research directions.

The second part of the research was based on a cross-sectional study, because we wanted to capture the issue addressed among Romanian students as well, and the bibliometric analysis highlighted the fact that only four works originate from Romania [51,52,53,54]. As we know, a cross-sectional study can be used in research to analyze data from a population at a single point in time, with an observational role [55]. In this way, we can identify the main characteristics of a group of people with reference to the phenomenon studied, we can perform a statistical analysis starting from the measured results, and we can obtain an estimate of the frequency, prevalence of attributes, or particularities of a phenomenon among the population. This type of observational research can provide us with data on the population’s exposure to the phenomenon studied, but also on the results of the exposure, i.e., association links and correlations of variables. To collect primary data, we used the questionnaire as a quantitative research instrument. The questionnaire was used, considering its multiple advantages, such as the rapid collection of results and the standardization that makes it possible to rigorously compare the results in statistical analysis, but also the fact that anonymity allows respondents to provide honest answers when the question is considered sensitive.

2.2. Data Source, Search Strategy, and Processing

2.2.1. Steps for Performing Bibliometric Analysis

Initially, a bibliometric analysis was conducted on research related to inappropriate smartphone use by students, with the aim of capturing the interest shown at a scientific level for the topic, but also regarding the evolution of research in the field.

As we know, a bibliometric analysis allows us to obtain qualitative as well as quantitative information [43]. To collect the information necessary for the analysis, the Web of Science (WOS) database was used, being recognized as an important and rigorous scientific database, which offers both a generous collection of works and integrated analysis tools [43,48,56]. Web of Science (WOS) is a database that records a multitude of bibliometric data, but also allows their sharing and thus becomes an extremely useful tool for researchers in carrying out bibliometric, comprehensive analyses, systematic reviews, etc., as it makes it possible to know the number of citations of an article or author, the number of publications of an author, how an article or journal is ranked, where an author comes from, and lots of other useful information.

For the search, the Web of Science (WOS) Core Collection was chosen, which includes the most important works published since 1975 and which provides a complete network of bibliometric data. The query of the Web of Science (WOS) Core Collection database was performed on 5 February 2025. The initial search in the literature was performed by the topic keyword “problematic smartphone use” and 1668 results were generated. Consulting the literature in the field, we found that specialists in the field use many other synonymous terms for our topic. Therefore, our search in the Web of Science Core Collection was moved from “Basic Search from the Documents search in the Documents tab” to “Advanced Search” to allow us to obtain a proper query builder. Thus, other synonymous terms/phrases are “problematic mobile phone use”, “smartphone addiction”, “mobile phone addiction”, “negative effects of smartphone use”, “negative effects of mobile phone use”, “smartphone overuse”, “mobile phone overuse”, and “PSU”. At this stage, the search query had the form:

TS = (problematic smartphone use OR problematic mobile phone use OR smartphone addiction OR mobile phone addiction OR negative effects of smartphone use OR negative effects of mobile phone use OR smartphone overuse OR mobile phone overuse OR PSU).

This search query generated 12,776 results. But, as the title of the article indicates, we want to analyze university students. Therefore, we will use a search operator or Boolean (AND) to include the topic “university students” in the search. Thus, the search query becomes:

(TS = (problematic smartphone use OR problematic mobile phone use OR smartphone addiction OR mobile phone addiction OR negative effects of smartphone use OR negative effects of mobile phone use OR smartphone overuse OR mobile phone overuse OR PSU)) AND TS = (university students).

With the new search query, the results generated were reduced to 1069. Up to this point, no filter (such as language filter, origin of publications, time periods, document types, etc.) had been added, as the goal was to have a comprehensive knowledge of the research landscape regarding the studied topic. We applied a document selection filter, type “article” (n = 966) for the rigor of the data analysis. The results found were used as the primary data source for analyzing problematic smartphone use among university students.

To ensure the accuracy of the data, we performed a manual double-check of the generated papers, so that the titles, abstracts, author keywords, and keywords plus were relevant to the researched topic. At the same time, papers incorrectly classified as articles (such as reviews) were eliminated. The verification process, as a mechanism used to ensure the reliability and validity of qualitative research, was carried out step by step, from general to specific. Thus, first the title was checked, then the abstract and keywords. If there were any doubts, the full text of the article was also accessed to ensure the validity of the data. On the other hand, where the phrase “university students”, but also “college students”, “college students from universities”, “students in universities”, etc., was found simultaneously in the title, abstract or keywords (especially for articles by Chinese authors), only papers where it could be verified that the minimum age limit of the students was 17 years old were accepted.

The remaining valid papers (n = 593) after the manual double-check were saved in a Marked List in the Web of Science account with the title “Selected works_PSU&University Students”. Subsequently, using the Export Record to Tab Delimited File from Web of Science (Record Content: Full Record and Cited References), we saved the papers in two lists named “PSU_File 1” (records from 1 to 500) and “PSU_File 2” (records from 501 to 593) to be used in bibliometric analysis using VOSviewer (release 1.6.20).

The steps of the literature search and analysis are summarized in Figure 1.

2.2.2. Cross-Sectional Study (Questionnaire)

Measure and Procedure: The questionnaire was developed by the author based on the analysis of the literature in the field, including validated and reliable measurement scales [15,22,26,30,57,58,59,60,61,62,63,64,65,66,67,68,69]. The content validity of the questionnaire was ensured by selecting and formulating items in line with the concepts and constructs identified in previously validated instruments and adapting them to the specific interest of this analysis. In addition, the questionnaire was translated into Romanian using clear and accessible language for the target population (students). The questionnaire was pre-tested on an initial pilot sample of 13 respondents (students), representatives of the target audience. Although the pilot sample was numerically limited, it was considered satisfactory for the purpose of this stage, namely, to identify any possible ambiguities, before addressing the main sample. Following the pre-test, the items were considered relevant for our study and clearly formulated, so that no changes to the questionnaire were needed.

Based on the existing questionnaires in the literature in the field, a questionnaire was adapted for Romanian students which corresponded to the interest of the current research. Thus, the questionnaire included 20 questions structured in 5 main sections: Section 1. Demographic data; Section 2. General data on smartphone use; Section 3. Habits and behaviors related to smartphone use; Section 4. Impact of smartphone use on learning and academic performance, and Section 5. Impact of smartphone use on stress levels, health, and interpersonal relationships. The data was collected through closed-ended items, consisting of single and multiple-choice questions on nominal and ordinal frequency scales. The study was conducted between 7 and 11 April 2025, and the questionnaire was physically handed out in the classrooms, being addressed to those who were present at the courses and seminars of the study’s holder in the mentioned week. Participants were informed about the purpose of the study, that participation was voluntary, and that responses were anonymous and confidential. The response rate to the questionnaire was 100% among participants due to the face-to-face approach, which allowed for the presentation of important aspects of the questionnaire, and ensured that participation was voluntary and that responses were anonymous and confidential. Two questionnaires were canceled because 1 question was unanswered.

Participants: Data collection took place at the Faculty of Economics and Business Administration of the University of Craiova, Romania. The questionnaire was addressed to Romanian students enrolled in full-time education, both female and male. Participants were students enrolled in their 2nd or 3rd year of their bachelor’s degree, specializing in Economics and International Affairs, including both the Romanian-language program and the English-language program. All students were eligible to participate in the study and were included if they agreed to participate. Thus, out of a total of 65 students present and included in the study, 63 participations (those who answered all questions) were validated, of which 27 were female students (42.9%) and 36 were male students (57.1%).

3. Results and Discussion

3.1. Bibliometric Investigation

3.1.1. Output Trends and Characteristics of Publications

By querying the Web of Science Core Collection database, the evolution of scientific publications that addressed the topic of problematic smartphone use among students over time was analyzed, as can be seen in Figure 2.

Thus, in the period between 2007 and 2025 (5 February) a total of 593 papers were published, which means an average of 33 papers per year. Evolutionarily, it is observed that in the period 2007–2015 the interest in the topic was lower, with only 19 papers published; this means an average of almost 2.38 per year and a share of almost 3.20 out of the total of 593 published papers. The issues addressed by researchers are closely correlated with mobile technology trends and the evolution of services that can be achieved using mobile phones. Therefore, in this early period, the authors analyzed the issue of excessive use of text messages among students [70], addictive behavior towards the internet, video games, shopping, studying of students, etc. [71,72], the relationship between psychological characteristics and mobile phone addiction of students [73], the factors that contribute to technological addiction and, in particular, to mobile phone addiction among students [74], the relationship between mobile phone addiction and sleep quality, depression, anxiety, etc., among students [30,75], the link between stress and smartphone addiction among students [76], the link between decreased academic performance and mobile phone use [6], and the link between loneliness, shyness, and mobile phone use among students [29]. Works related to phubbing are also appearing, as the sum of virtual addictions, including smartphone addiction [40]. At the same time, various versions of the Smartphone Addiction Scale are starting to be validated at the national level [63,64,65].

In the second period between 2016 and 2025, interest began to grow, with 574 papers published; this means an average of 57.5 per year and a share of almost 96.8 of the total publications. It is further shown that students with psychosocial problems are vulnerable to excessive use of cyber-technological devices—including a smartphone [31,77,78,79]. The evidence that smartphone addiction leads to decreased academic performance, quality of life, and increased stress is evident [32,80,81,82,83]. More and more versions of the National Technology Addiction Scales are being validated [66,67,68,69]. In these recent 10 years included in the reference period of our analysis, various phenomena and specific situations related to excessive smartphone use among students have been captured; terms such as “cyberloafing”, “nomophobia”, “cyberbullying”, “fear of missing out”, and “bedtime procrastination” are gaining notoriety [17,34,36,84,85,86]. Other works have addressed the link between smartphone addiction and physical health or physical activity [87,88], but also in relation to the COVID-19 pandemic period [89,90,91,92,93].

About 94.6% of the published papers are written in English (n = 561), about 3.7% are written in Spanish (n = 22), and the remaining just over 1.7% are written in Turkish (n = 5), Greek (n = 1), Korean (n = 1), Polish (n = 1), Portuguese (n = 1), and Russian (n = 1), as can be seen in Figure 3.

As can be seen in

Table 1. Brief bibliometric overview of publications in the field.

Indicator	2007–2015	2016–2025	Total (2007–2025)
Articles	19	574	593
Authors	60	2213	2255
Publishers	11	129	132
Citations (times cited)	3208	11,923	15,131
Citations (average per year)	200.5	1192.3	945.69
Countries/Regions	13	77	77
Research areas	11	45	45
Authors/article (average)	3.16	3.86	3.80
Authors/country (average)	4.62	28.74	29.29
Citations/article (average)	168.84	20.77	25.52
Citations/country (average)	246.8	154.84	196.5

Source: author’s own elaboration using data provided by WOS.

, the number of articles on problematic smartphone use among students increased considerably in the period 2016–2025 compared to the period 2007–2015, which shows the increased interest in the issue, especially recently, in the context of a digital, informational era. At the same time, the growth is impressive among authors, countries/regions, and publishers. Regarding productivity metrics, it is observed that the average authors/article has increased, which signifies a positive trend of collaboration between authors, but more promising is the authors/country ratio, which increased from 4.62 to 28.74. The research topic has been addressed in more and more countries and regions with the spread of the negative phenomenon of mobile phone addiction and the increase in their problematic use among the population, especially among young people and students. Therefore, a diversification of the academic landscape is noted in the period 2016–2025, but especially recently. Two indicators had a different, decreasing trend: citations/article (from 168.84 to 20.77) and citations/country (from 246.8 to 154.84). The explanations are multiple, firstly numerical, that is, in the recent period (2016–2025) there were impressive increases in all the mentioned indicators, but the share was higher in terms of the number of authors and the number of countries compared to the number of citations. Secondly, it is related to the time horizon; older works have had more time to be analyzed and cited compared to the most recent ones. A third explanation may be related to the changing academic trend towards the issues addressed, but it is too early to be sure of this; only time will tell.

3.1.2. Analysis of the Main Countries with the Most Publications

Problematic smartphone use among students involves excessive or inappropriate use of the smartphone in everyday life, but also in academic activity, and is a pattern of behaviors that negatively influences mental health (anxiety, depression, chronic fatigue, insomnia, etc.), physical health (vision problems, muscle pain, spine problems, headaches, etc.), and leads to decreased academic performance, neglect of interpersonal relationships, and social isolation, and therefore to a decrease in the quality of life, overall. Therefore, young people and students are the age group most exposed and thus most vulnerable to the negative effects of using technology and digital devices (laptops, tablets, mobile phones, smartwatches) because they are the most active users, dedicating a large part of their time to online browsing, whether for socializing, studying, or entertainment.

In this regard, the researchers were interested in addressing this topic in order to obtain statistical data and pertinent information regarding the excessive exposure of young people to mobile technology and the excessive use of digital devices, the impact on learning and academic performance (considering digital multitasking, distraction due to notifications, obsession with constantly checking the phone, excessive use of AI systems), the negative effects on physical and mental health (incorrect posture, eye fatigue, lack of interest in physical exercise, sleep disorders), the negative effects on social relationships (social isolation, loss of interest and ability to develop interpersonal relationships), and the intensification of the phenomenon of digital addiction (FOMO—Fear of Missing Out, nomophobia—fear of not having access to the mobile phone or its services). Other authors were interested in providing tools to measure addiction to technology and mobile devices (Smartphone Addiction Scale, Internet Addiction Test, Social Media Addiction Scale, etc.) and finding solutions for a balanced use of digital devices, as well as prevention and awareness programs and measures among young people.

The analysis of the distribution of publications by country generated a total of 77 countries/regions (Figure 4). Of these, most publications referring to excessive smartphone use among students were identified as originating from China (n = 145). This means that almost 25% of the articles related to the analyzed issue originated from China. Statistical data such as the number of internet users being 1.1 billion, the number of mobile internet users 1.096 billion, a share of 99.7% of internet users do so on mobile phones, and an average weekly internet use of 29.0 h among the general population [94], of course, can be a solid basis for analysis in the field, and will also draw attention to the analysis of the negative effects of using digital devices among the population, especially since the phenomenon affects the entirety of society. At the same time, in addition to these statistical data, we must not forget that China treats the issue of digital addiction as a public health issue, and the large number of users addicted to social networks and mobile games, including minors who use the phone at night before going to sleep, has led the Chinese government to adopt various regulations to ensure appropriate content for them (such as Decree No. 766 “Regulations on the Protection of Minors on the Internet” [95], but also proposals to reduce the time spent online, such as a 2 h limit for the 16–18 age group or a blocking of apps between 10:00 p.m. and 6:00 a.m. [96]. Corroborating all the above, we must mention that interest in the topic has shown a constant and growing trend in recent years in China, as shown by the number of articles identified (9 articles in 2019, 15 articles in 2020, 18 articles in 2021, 30 articles each in 2022 and 2023, and 34 articles in 2024).

Turkey is the second country of origin of publications in the field, with a total of 107 articles. With a population of approximately 85.8 million in 2024, Turkey has recorded a continuous increase in the share of the population using the internet (88.8%) [97]. The most used applications were WhatsApp (86.2% of the population), YouTube (71.3%), and Instagram (65.4%) according to data provided by the Turkish Statistical Institute [97]. According to [98], the highest share of the population using a smartphone in Turkey corresponds to the 18–24 age group (49.1%), which is exactly the age group that belongs to students. Also, recent data shows that the Turkish population spends over 4 h per day on their smartphones.

England and the United States are the next countries of origin of the articles, with 49 and 45 articles, respectively. According to [99], the number of mobile subscriptions in the UK exceeded 116 million in 2023, and OTT messaging services (WhatsApp, iMessage, Facebook Messenger) are recording a constant growth, to the detriment of traditional SMS services. In the same vein, a YouGov survey from 2023 [100] shows that 41% of respondents believe that they spend too much time on their phones, the majority of those who gave this answer (63%) being from the 18–24 age group. At the same time, most respondents (67%) claimed that they do nothing to change this situation (58% being from the 18–24 age group). Studies funded by the NIHR Maudsley Biomedical Research Centre show that among teenagers in England, there is a high rate of problematic smartphone use; in addition, young people develop fears and mental illnesses [101].

Regarding the US population, data published by the Pew Research Center in 2024 [102] shows that 91% of those who have a mobile phone own a smartphone (this means that 9 out of 10 Americans have a smartphone). Of the 99% of phone owners included in the 18–29 age group, 98% have a smartphone and a share of 21% of this age group is shown to have a smartphone addiction, being the largest and most exposed category of the population. The most recent data shows that the American population has come to spend over four to five hours a day on their smartphone (even over 6 h in the case of Gen Z).

The next countries of origin of the articles in the ranking are Saudi Arabia and Spain (with 38 articles each), Iran (29 articles), Malaysia (25 articles), India (22 articles), and Pakistan and South Korea (with 21 articles each). Countries that also have more than 10 articles are Taiwan (19 articles), Australia (18 articles), Egypt and Italy (15 articles each), Brazil (14 articles), Canada (13 articles), Germany (11 articles), and Bangladesh and Sweden (10 articles each).

This visualization of the network shows us a wide spread of the countries of origin of these articles worldwide due to the increased general interest of specialists in the field regarding the topic, considering both the propagation of communication and information technology, but also the increasing use of digital devices in all daily activities of the population; these phenomena are accompanied by specific negative effects, as previously mentioned in the paper. A propagation of the research shows the existing trend of the negative effects of smartphone use, in addition to all its benefits, among the general population, especially young people, adolescents, and students alike. It can be noted, however, how many countries are associated with the research of this topic, offering opportunities for collaboration between states and between researchers, depending on availability and interest: some states can benefit from greater funding, while others manage to obtain superior research results through the technology used in the research, but also the specialists involved. We also mention that these researched everyday realities involve interest from all parties involved, from researchers, specialists in the field, and technological capabilities of giants in the technology industry, to national and international priorities of governments, but also challenges and solutions from international bodies and organizations.

3.1.3. Co-Authorship Analysis

A.

By country

For the analysis of co-authorship by country, it was established that the minimum number of articles of a country is equal to 1 because we want to be able to analyze the general situation of all publications.

Thus, of the 77 states/regions identified, the state with the highest total link strength (TLS) is England (TLS = 93) with a total of 49 articles and collaborations with 33 countries (Figure 5). Therefore, its connections are the strongest, as is the weighted sum of the collaborations. The 2nd and 3rd places are occupied by China (TLS = 89, collaborations with 22 countries) with a total of 145 articles and the USA (TLS = 67, collaborations with 34 countries) with a total of 45 articles. The next places are occupied by Taiwan (TLS = 36) with a total of 18 articles and collaborations with 11 countries, Saudi Arabia (TLS = 34) with a total of 38 articles and collaborations with 18 countries and Sweden (TLS = 33) with a total of 10 articles and collaborations with 11 countries. In addition to these states that are included in the first places of the total link strength of co-authorship ranking by country, it is interesting to mention in our analysis that there are 2 others, contrasting categories. On the one hand, we have states with a small number of articles, but with a high total link strength (Bahrain, D = 2, TLS = 13; Netherlands, D = 3, TLS = 12; Jordan, D = 9, TLS = 20), which shows a close collaboration, multiple co-authors of different nationalities, i.e., a high degree of connectivity at the international level. On the other hand, we have countries with a large number of articles, but with a low total link strength (Spain, D = 38, TLS = 9), which shows us a large volume of published documents, but which are more aimed at the national level, not the international one, in this case the collaborations being limited and fragmented. Ten of our countries (with a number of articles between one and four) have a total link strength equal to zero (Cyprus, Iraq, Israel, Kazakhstan, Nigeria, Peru, Russia, Singapore, Sudan, and Vietnam), so the corresponding articles are made without co-authors from other countries; they are not included in the graph above.

B.

By authors

The statistical analysis of the authors provides us with valuable information about the representative researchers active in the field, those who have given the greatest interest in researching the topic of problematic smartphone use among students, as well as information about the collaboration between the authors. For the co-authorship analysis, we chose authors as the unit of measurement and a minimum number of documents for each author equal to two. Thus, from a total of 2255 entries (authors), the selection resulted in a map with 210 authors. For the overlay visualization scale, we selected the number of documents for weights and the average of citations for scores, according to Figure 6.

Considering that each node means an author and that the size of a node, in our case, provides indications regarding the number of publications, it can be concluded that Griffiths Mark D. is the most representative author in the analyzed network, being the author with the most publications (p = 26) and with the most citations (C = 1501), but also with total link strength (TLS = 78). This author has 33 links. The next most representative author is Lin, Chung-Ying, with a total number of 10 documents, 701 citations, 15 links, and a total link strength equal to 48. Pakpour, Amir H is an author with 7 documents, 644 citations, and a total link strength equal to 36. The fourth author mentioned in our ranking, according to the number of publications and total link strength, as can be seen in

Table 2. The most prolific authors by number of publications.

Author	Publications (Record Count)	% of 593 Documents	Citations	Average Number of Citations
Griffiths, Mark D.	26	4.384	1501	57.73
Lin, Chung-Ying	10	1.686	701	70.10
Pakpour, Amir H.	7	1.180	644	92.00
Mei, Songli	6	1.012	302	50.33

Source: author’s own processing.

, is Mei, Songli with 6 documents, 302 citations, and a total link strength equal to 17.

All these authors are in proximity, as we can see from the proximity of the nodes in the bibliometric map, which suggests that they have common interests in terms of the research topics addressed. At the extreme end, authors who are not very active in terms of collaborations are located, but this does not mean that they have not published or that they are not important in the research field. In this sense, we mention the author Samaha Maya who, although he has only one link and total link strength equal to four, his four documents have accumulated 1254 citations and an average number of citations of 315.50. In the same situation is the author Hawi Nazir S., who although has only one link, his four documents have accumulated 1254 citations and an average number of citations of 313.50.

3.1.4. Keywords Co-Occurrence Analysis

For keywords co-occurrence analysis, we chose all keywords as the unit of measurement, then we considered full counting as the counting method, and we have as a threshold level of a minimum of 10 occurrences for a keyword. Thus, the data extracted from the Web of Science Core Collection revealed a total of 1723 keywords (both author keywords and keywords plus), and according to our selections presented above, a map containing 120 keywords was generated (Figure 7). Each node corresponds to a term, and the larger the node, the higher the occurrences number. The lines are connections between terms, which show us how often those terms appear together. In the present situation, the term with the most occurrences is “smartphone addiction” (Occ. = 212), and in the case of our research topic this refers to the addiction of students to their smartphones, the use of their mobile phones excessively, but sometimes incorrectly, with a negative impact on attention, concentration, learning, and therefore overall academic performance. The negative effects extend to the physical and mental health of students, but also to social relationships. So, when we talk about student addiction, terms such as “addiction” (Occ. = 196, second place in terms of occurrences), “internet addiction” (Occ. = 99), “mobile phone addiction” (Occ. = 66), “problematic smartphone use” (Occ. = 58), “problematic internet use” (Occ. = 34), “self-control” (Occ. = 27), “social media addiction” (Occ. = 24), “social networking” (Occ. = 16), and “addictive behavior” (Occ. = 10) were used. The most common terms when the research targeted students’ academic performance were “academic-performance” (Occ. = 35)/“academic performance” (Occ. = 29), “performance” (Occ. = 25), “engagement” (Occ. = 13), “motivation” (Occ. = 13), and “education” (Occ. = 10). Regarding the mental and physical health of students, as a result of problematic smartphone use, we encounter terms such as “anxiety” (Occ. = 179), “depression” (Occ. = 165), “sleep quality” (Occ. = 80), “stress” (Occ. = 74), “nomophobia” (Occ. = 46), “loneliness” (Occ. = 34), “depressive symptoms” (Occ. = 23), “mental health” (Occ. = 22), “insomnia” (Occ. = 13), and “musculoskeletal pain” (Occ. = 12). Nor should we omit terms such as “university students” (Occ. = 96) or “university-students” (Occ. = 50), “adolescents” (Occ. = 139), “smartphone” (Occ. = 101), or “mobile phone” (Occ. = 80), etc., which are indispensable in the literature on the topic.

Other relevant terms in keywords co-occurrence analysis were “prevalence” (Occ. = 69), “scale” (Occ. = 55), “reliability” (Occ. = 52), “validity” (Occ. = 44), “model” (Occ. = 39), and “predictors” (Occ. = 31) and are specific to those studies that aimed to develop or translate measurements/scales of problematic behaviors of students related to the use of phones, laptops, internet, social networks, etc. Scales for measuring problematic smartphone use are extremely useful to identify those people at risk of addiction, so that it is possible to take measures as early as possible, including when excessive use has led to health problems (whether physical, mental, or social). In addition to potential subjects at risk of addiction, other categories of people also benefit from these scales, through the structured and validated data provided; we mention psychologists, doctors of various specialties, educators, teachers, researchers.

The 120 keywords included in the clustering map were grouped into four clusters: cluster 1, red, contains 43 items; cluster 2, green, contains 31 items; cluster 3, blue, contains 28 items; and cluster 4, yellow, contains 18 items. Cluster 1 (red) is the largest of the four, containing keywords specific to the research topic “The impact of problematic smartphone use on students’ academic performance”. Cluster 2 (green) contains keywords related to the topic “Mental and physical health problems of students and young people”. Cluster 3 (blue) includes keywords related to the topic “Smartphone addiction and related factors”. Cluster 4 (yellow) consists of keywords specific to the topic “Stress and psychological distress among young people”. All this information, as well as a selection of the most important keywords in each cluster and the number of occurrences for each, are included in

Table 3. Research topics and keywords within clusters.

Cluster No.	Research Topic	Major Keywords and Occurrences
Cluster 1 (Red)	The impact of problematic smartphone use on students’ academic performance	Smartphone addiction (Occ. = 212) Internet addiction (Occ. = 99) University students (Occ. = 96) Academic performance/Academic-performance (Occ. = 29/35) Nomophobia (Occ. = 46) Social media (Occ. = 35) Problematic smartphone use (Occ. = 34) Satisfaction (Occ. = 33) Performance (Occ. = 25)
Cluster 2 (Green)	Mental and physical health problems of students and young people	Anxiety (Occ. = 179) Depression (Occ. = 165) Sleep quality (Occ. = 80) Prevalence (Occ. = 69) University-students (Occ. = 50) Symptoms (Occ. = 50) Mental health/Mental-health (Occ. = 22 + 19) Physical activity/Physical-activity (Occ. = 20 + 10)
Cluster 3 (Blue)	Smartphone addiction and related factors	Addiction (Occ. = 196) Smartphone (Occ. = 101) Mobile phone (Occ. = 80) Personality (Occ. = 50) Behavior (Occ. = 38) Problematic internet (Occ. = 25) Dependence (Occ. = 15)
Cluster 4 (Yellow)	Stress and psychological distress among young people	Adolescents (Occ. = 139) Stress (Occ. = 74) Depressive symptoms (Occ. = 53) Loneliness (Occ. = 34) Self-control (Occ. = 27)

Source: author’s own processing using VOSviewer.

.

As we can see from the data related to keyword co-occurrence, although the research in the field varies, all these terms are interconnected, so that the themes presented as central to the four clusters are interconnected, in a close relationship of mutual dependence. Indeed, the major theme is that of problematic smartphone use, that is, addiction to its use by students. But with problematic smartphone use, this addiction to smartphones is also linked to education, students’ academic performance, mental and physical problems that have arisen, and problematic use of the internet, social networks, and other addictions. We also conclude that the overlap in some places of the four clusters indicates that the treatment of the theme should not be in a separate manner, but interconnected, simultaneously with other themes/domains. Therefore, certain terms were identified as belonging to several clusters: smartphone addiction/mobile phone addiction appears in clusters 1 and 4, smartphone use/smartphone usage appears in clusters 1 and 4, problematic internet/problematic internet use in clusters 1 and 3, etc. All these meeting points of the clusters offer interdisciplinary interest in terms of the complexity of the researched topic and at the same time offer directions for future research, either by identifying gaps in the literature or by addressing new topics of interest.

3.1.5. Analysis of the Most Cited Papers

For the bibliometric analysis of citations, we chose “documents” as the unit of measurement and set a threshold for the number of citations per document equal to at least five. Out of the 593 items, according to the established selection criteria, 354 items met the conditions. To highlight the situation as clearly as possible, we accepted VOSviewer’s recommendation to omit 16 documents in creating the map because they were not connected to each other, and thus a map with 338 documents was generated, showing connected items, as can be seen in Figure 8.

The bibliometric analysis of the most cited works is a barometer of the main research directions of the topic, considering that research in the field will generate not only knowledge of the topic, but will also contribute to the dissemination and valorization of the results generated by the respective research. With strict reference to the research on the problematic use of smartphones among students, we can conclude that the knowledge of the most cited works offers a dashboard of the current situation, the categories of subjects at risk of addiction, and the trends in the field. In addition, it contributes to the creation and development of collaborative relationships at national, international, and institutional levels of researchers in the fields (whether we are talking about teachers, IT specialists, pedagogues, doctors, state institutions, NGOs, etc.), assuming the study of the issue is unidisciplinary, multidisciplinary, interdisciplinary, depending on the interest or the gap identified in the literature. Subsequently, all this research will serve for future practices and theories, which will allow us to solve the problems that have arisen among students due to the abusive, problematic use of smartphones in their educational and daily activities, that is, starting from those problems related to academic performance to health problems, addictions, and psychological suffering.

In

Table 4. The 10 most cited publications.

Publication	Corresponding Author	Source, Year	Citations
			Total	Average/ Year
Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students [30]	Demirci, Kadir	Journal of Behavioral Addictions, 2015	817	74.27
Relationships among smartphone addiction, stress, academic performance, and satisfaction with life [32]	Samaha, Maya	Computers in Human Behavior, 2016	697	69.7
The relationships between behavioral addictions and the five-factor model of personality [72]	Andreassen, Cecilie Schou	Journal of Behavioral Addictions, 2013	352	27.08
Linking Loneliness, Shyness, Smartphone Addiction Symptoms, and Patterns of Smartphone Use to Social Capital [29]	Leung, Louis	Social Science Computer Review, 2015	342	31.09
Depression, anxiety, and smartphone addiction in university students-A cross sectional study [81]	Boumosleh, Jocelyne Matar	PLoS One, 2017	334	37.11
A model of the relationship between psychological characteristics, mobile phone addiction and use of mobile phones by Taiwanese university female students [73]	Chiu, Shao-I.	Computers in Human Behavior, 2012	325	23.21
Smartphone addiction and its relationship with social anxiety and loneliness [31]	Enez Darcin, Asli	Behaviour & Information Technology, 2016	259	25.9
The relationship between life stress and smartphone addiction on taiwanese university student: A mediation model of learning self-Efficacy and social self-Efficacy [76]	Chiu, Shao-I.	Computers in Human Behavior, 2014	234	19.5
To excel or not to excel: Strong evidence on the adverse effect of smartphone addiction on academic performance [80]	Hawi, Nazir S.	Computers & Education, 2016	231	23.1
Determinants of phubbing, which is the sum of many virtual addictions: A structural equation model [63]	Karadag, Engin	Journal of Behavioral Addictions, 2015	230	20.91

Source: author’s own processing using Web of Science Core Collection database.

, we have selected the 10 most cited papers on problematic smartphone use among students. Thus, as can be seen in the table, the most cited paper according to Web of Science, with 817 citations, is “Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students” by Demirci Kadir, Akgönül Mehmet, and Akpinar Abdullah published in Journal of Behavioral Addictions. They analyzed the correlation between daytime dysfunctions, sleep quality, anxiety, depression, and smartphone use among students [30]. The paper “Relationships among smartphone addiction, stress, academic performance, and satisfaction with life” by Samaha Maya and Hawi Nazir S. has accumulated 697 citations according to WOS. Published in the journal Computers in Human Behavior, the paper examines the bi-directional relationship between smartphone addiction and quality of life, stress, and academic performance [32]. “The relationships between behavioral addictions and the five-factor model of personality” is the third paper, with 352 citations, published in the Journal of Behavioral Addictions by Andreassen Cecilie Schou, Griffiths Mark, Gjertsen Siri Renate, Krossbakken Elfrid, Kvam Siri, and Pallesen Stale. They extended the research by addressing the correlation between several addictive behaviors and the dimensions of the five-factor model of personality [72]. In fourth place is the paper “Linking Loneliness, Shyness, Smartphone Addiction Symptoms, and Patterns of Smartphone Use to Social Capital”, with 342 citations, published by the authors Bian Mengwei and Leung Louis in the journal Social Science Computer Review, which attempts to capture the symptoms of smartphone addiction by analyzing the link between the psychological attributes of the student group and smartphone usage patterns [29]. The paper “Depression, anxiety, and smartphone addiction in university students-A cross-sectional study” totaled 334 citations and belongs to the authors Boumosleh Jocelyne Matar and Jaalouk Doris. Published in PLoS One, this is the authors’ proposal to observe the prevalence of smartphone addiction symptoms, but also a study on the link between depression, anxiety, and smartphone addiction by using different variables of an academic, psychological, and social nature [81]. Hong Fu-Yuan, Chiu Shao-I., and Huang Der-Hsiang have accumulated 325 citations for the paper “A model of the relationship between psychological characteristics, mobile phone addiction and use of mobile phones by Taiwanese university female students” published in Computers in Human Behavior. They also found a link between smartphone use, addiction, and psychological characteristics, but among Taiwanese female students [73]. With 259 citations, the paper “Smartphone addiction and its relationship with social anxiety and loneliness” investigates the link between excessive smartphone use by students and social phobia [31]. Chiu Shao-I. accumulated 234 citations for the paper “The relationship between life stress and smartphone addiction on Taiwanese university student: A mediation model of learning self-Efficacy and social self-Efficacy” and wanted to analyze various protective factors which should be considered in intervention programs for smartphone addiction [76]. The article “To excel or not to excel: Strong evidence on the adverse effect of smartphone addiction on academic performance” belongs to the authors Hawi Nazir S. and Samaha Maya; the analysis on the relationship between academic performance and smartphone addiction totaled 231 citations [80]. Our last mention in this ranking is the article “Determinants of phubbing, which is the sum of many virtual addictions: A structural equation model”. It collected 230 citations, being a specific analysis of phubbing, that is, those situations in which phone addiction is so high that the smartphone owner constantly looks at their phone, uses it, and omits their interlocutor during a conversation [63].

Through the above works, we can observe two important aspects of their bibliometric analysis. On the one hand, the fact that all the works cited as being ranked first are 10–14 years old; so, we are aware that the recognition of a work does not appear immediately, but it takes a period for them to be read, become visible, and be recognized by the academic community. Subsequently, they are integrated into other research and in this way a well-defined, complex and harmonious field is built, and the value is evident in the medium and long term. A second aspect that we can conclude is related to the interdisciplinarity of the topic. We can talk about a combination of computer science (when algorithms are used to detect excessive smartphone use or we are offered technological options to avoid addiction), educational sciences (whenever we link problematic smartphone use with academic performance, learning, logical correlations, or we are offered technological options to integrate smartphones into the educational process), psychology (many authors link smartphone use with anxiety problems, depression, concentration problems, cognitive problems, stress), medicine (health problems caused by excessive smartphone use such as back pain, visual problems, sedentary lifestyle, decreased sleep quality), and social sciences (addiction to social networks, affecting interpersonal relationships, phubbing), but also with economics (the link between excessive use and decreased productivity, inefficient multitasking, influencing consumer behavior), etc. The complexity of the topic implies an interdisciplinary, multidisciplinary treatment to ensure a full understanding of the impact and implications of this defective, harmful behavior for students and beyond, so a single scientific perspective would not be sufficient.

Thus, we must recognize the scientific importance of all works in the field, even if they could not be captured in our table. Just because they did not receive more citations than the works mentioned does not mean that they do not have an essential, critical role in the scientific substantiation of the topic of problematic smartphone use among students and do not support efforts to identify pertinent solutions to the problems that have arisen.

3.2. The “Voice” of Romanian Students

It should be emphasized that this exploratory study provides a preliminary insight into the situation of smartphone use among some Romanian students, particularly given that the bibliometric analysis of the literature in the field revealed only four studies originating from Romania. So, at present, empirical data on this population remain scarce in the literature.

The relatively small sample size (n = 63), drawn from a single faculty, represents a limitation that restricts the generalizability of the findings. Therefore, the results should be interpreted with caution and not extrapolated to the broader student population. For future research, we recommend employing larger and more diverse samples to validate and generalize the conclusions. However, we cannot neglect that the data obtained in this part of the study are valuable for the researched issue, and the exploratory approach completing the previous bibliometric investigation.

The first part of the questionnaire included three questions regarding the demographic characteristics of the responding students: age, gender, and residence (

Table 5. Demographic characteristics for the sample (n = 63 students).

Variable	Answer Choices	Frequency	Percentage (%)
Age (years) M ± SD (21 ± 1.24)	19	0	0.00
	20	23	36.51
	21	28	44.44
	22	10	15.87
	23–25	0	0.00
	25+	2	3.17
Gender	Male	36	57.14
	Female	27	42.86
Residence	Urban	46	73.02
	Rural	17	26.98

). Of the 63 students from the Economics and International Affairs bachelor’s degree program (years 2 and 3 of study) in full-time education, 27 were female students (42.9%) and 36 male students (57.1%), with an average age of 21 years (SD = 1.24), ranging from a minimum of 20 years to a maximum of 27 years. The respondents were predominantly male (n = 36, % = 57.1) and predominantly from urban areas (n = 46, % = 73.0).

The next two sections of the questionnaire included questions related to general aspects of smartphone use in students’ daily lives, including smartphone habits and behaviors; the questions and answers are presented in

Table 6. Distribution of variables related to general smartphone usage, including smartphone usage habits and behaviors.

Variable	Answer Choices	Frequency	Percentage (%)
How many years have you had a smartphone?	<3 years	0	0.00
	4–5 years	0	0.00
	6–7 years	6	9.52
	8–9 years	15	23.81
	>9 years	42	66.67
What is the average daily smartphone usage?	<1 h	0	0.00
	1–3 h	7	11.11
	4–7 h	45	71.43
	>7 h	11	17.46
What are the main activities on your smartphone (you can choose multiple answers)?	Call & SMS	52	82.54
	Internet browsing	53	84.13
	Academic preparation	16	25.40
	Socializing	54	85.71
	Games	19	30.16
	Entertainment	22	34.92
	Other activities …	1 (work)	1.59
How often do you check your smartphone per day (notifications, social media, etc.)?	Several times an hour	51	80.95
	Once an hour	8	12.70
	Every 1–2 h	2	3.17
	Every few hours	2	3.17
	Once a day	0	0.00
Do you feel agitated/nervous/stressed when you don’t have access to your smartphone?	Not at all	43	68.25
	To a certain degree	19	30.16
	Completely	1	1.59
Have you ever felt like you couldn’t control the time you spent on your smartphone?	Never	9	14.29
	Sometimes	40	63.49
	Often	14	22.22
	Always	0	0.00
Have you ever felt the need to reduce the time you spend on your smartphone?	Never	6	9.52
	Sometimes	25	39.68
	Often	20	31.75
	Very often	12	19.05

. Thus, according to the responses of the students in our sample, the majority have owned a smartphone for over 9 years (n = 42, % = 66.67) and the majority (n = 45, % = 71.43) spend an average of between 4 and 7 h per day on their smartphone. Moreover, there is also a share of 17.46% of students who declared that they spend even more than 7 h per day on their smartphone. Thus, the students in our sample have a high and very high level of average daily smartphone use, being intensive users, which can be considered problematic use, which can lead to compulsive smartphone use behavior and to addiction. These increased levels of smartphone use identified through the responses received from the surveyed students are consistent with previous research, which mentions that the young population, especially university students, are intensive smartphone users [103,104,105] and highlights problematic smartphone use [80,82,84]. A share of 80.95% (n = 51) of the students in our sample stated that they check their smartphone several times an hour. For them, checking their smartphone so frequently can lead to loss of attention and concentration, with a negative impact on learning and productivity. Frequent smartphone checking among students identified through the application of the questionnaire corresponds to previous international research, showing a lack of self-control, affecting attention, concentration, and learning [25,66,86,106]. The use can be considered even more problematic as we observe according to the students’ responses that the main activities on the smartphone are socializing (n = 54, % = 85.71), internet browsing (n = 53, % = 84.13), and calls and SMS (n = 52, % = 82.54), while academic preparation ranks last (n = 16, % = 25.40). The findings are consistent with previous findings in the literature, where smartphone use for academic preparation is much lower than its use for social media and leisure, with negative implications for academic performance and well-being [80,87].

Interestingly, although 68.25% of students (n = 43) responded that they do not feel agitated or nervous if they do not have access to their smartphone, almost 86% (n = 54) said that they sometimes cannot control the time spent on their smartphone (Sometimes: n = 40, % = 63.49; Often: n = 14, % = 22.22) and over 90% (n = 57) feel the need to reduce the time spent on their smartphone (Sometimes: n = 25, % = 39.68; Often: n = 20, % = 31.75; Very often: n = 12; % = 19.05). Combining these results can be interpreted as a lack of addiction, but an existence of compulsive behavior, which suggests a self-control conflict. Thus, based on the responses received from the sample, we can observe a difficulty in managing certain situations, a self-control conflict, which contributes to the development of disruptive behaviors, i.e., exactly what other studies have identified as compulsive smartphone use among students [77,107]. Studies show that there is a link between smartphone addiction and low self-control [106], and those with a low self-control capacity are those who respond immediately to mobile notifications [108]. Thus, studies suggest that self-control could predict mobile phone overuse through interpersonal and transactional use patterns [107].

Section 4 of the questionnaire included variables related to the influence of smartphones on learning and academic performance, as can be seen in

Table 7. Distribution of variables related to the impact of smartphone use and its impact on learning and academic performance.

Variable	Answer Choices	Frequency	Percentage (%)
Do you think smartphone use influences your academic performance?	Yes, positively. It helps me be more efficient in learning.	19	30.16
	No. I don’t think it influences my academic performance.	26	41.27
	Yes, negatively. It distracts me and prevents me from completing my duties on time.	18	28.57
	Other answers …	0	0.00
Do you ever lose focus in classes and seminars because of your smartphone (checking, notifications)?	Never	0	0.00
	Rarely	15	23.81
	Sometimes	40	63.49
	Very often	8	12.70
Has a teacher/colleague ever remarked to you that you’re not paying attention during class because of your smartphone use?	Never	24	38.10
	Rarely	29	46.03
	Sometimes	10	15.87
	Very often	0	0.00
Do you experience a lack of attention/concentration while preparing lessons/homework or do you procrastinate doing them because of your smartphone?	Never	18	28.57
	Rarely	18	28.57
	Sometimes	25	39.68
	Very often	2	3.17

. Most students who participated in our study do not consider that smartphone use influences their learning and academic performance (n = 26, % = 41.27). Otherwise, perceptions are divided between those who consider smartphones a useful tool in learning and those who perceive it as a source of distraction; the weights are almost equal between those who consider smartphones to contribute to the efficiency of learning (n = 19, % = 30.16) and those who consider that smartphone use distracts them from learning and prevents them from completing their duties on time (n = 18, % = 28.57). These divided perceptions regarding smartphone use are also observed in other studies [8,9]. It is worrying that almost a third of the surveyed students stated that they are distracted in academic activity due to smartphone use, which reveals a problem of smartphone use in the educational, academic context. Supporting this concern are the data from the questionnaire, according to which over 71% of respondents (n = 45) stated that they sometimes lose concentration or postpone completing homework (Rarely: n = 18, % = 28.57; Sometimes: n = 25, % = 39.68; Very often: n = 2, % = 3.17). All surveyed students stated that they lose attention in class to a certain extent due to smartphone use (Rarely: n = 15, % = 23.81; Sometimes: n = 40, % = 63.49; Very often: n = 8, % = 12.70) and almost 62% of students responded that they were observed in class at least once due to smartphone use (Rarely: n = 29, % = 46.03; Sometimes: n = 10, % = 15.87). Although the results should be interpreted with caution, given the sample size and specificity, they are consistent with the results of previous studies in the literature in the field [5,6,7,11].

The last section of the questionnaire followed the students’ point of view regarding the influence of smartphones on stress levels, health, and interpersonal relationships, as seen in

Table 8. Variable distribution related to the impact of smartphone use and its effects on stress, health, and interpersonal relationships.

Variable	Answer choices	Frequency	Percentage (%)
Do you think you’ve been stressed lately?	Not at all	4	6.35
	To a small extent	19	30.16
	To a certain extent	27	42.86
	To a large extent	9	14.29
	Extremely stressed	4	6.35
Do you think that the time spent on your smartphone influences your stress level?	No	39	61.90
	To a small extent	16	25.40
	To a large extent	3	4.76
	Yes	5	7.94
Have you experienced moments of restlessness/anxiety/depression due to frequent notifications or constant exposure to social media (through social comparisons)?	Never	41	65.08
	Rarely	9	14.29
	Sometimes	11	17.46
	Very often	2	3.17
Have you had any health problems lately that you can attribute to excessive smartphone use (you can choose multiple answers)?	I am not aware of any health problems	41	65.08
	Muscle and joint pain	6	9.53
	Neck and back pain	1	1.59
	Eye fatigue/vision problems	14	22.22
	Sleep disorders/insomnia	5	7.94
Do your family or friends criticize you for spending too much time on your smartphone?	Never	35	55.55
	Rarely	14	22.22
	Sometimes	11	17.46
	Very often	3	4.76
Have you ever felt that spending time on your smartphone is more enjoyable than spending time with family/friends/colleagues?	Never	35	55.55
	Rarely	20	31.75
	Sometimes	6	9.53
	Very often	2	3.17

. An extremely high share of this sample (n = 59, % = 93.66) feel stressed to some extent, but most claim that the time spent on smartphones does not influence stress levels (n = 39, % = 61.90). Undeniably, smartphone use influences stress levels and health, as studies in the field conclude [30,32,33], but the effect can be direct or indirect, which can mislead students’ perception of its influence. We should not omit the third of surveyed students who perceive a link between stress levels and time spent on smartphones; the causes may include overstimulation due to multitasking, inability to mentally disconnect, insomnia due to intensive smartphone use, frustration and fatigue due to games, and restlessness and anxiety due to exposure to social media. Even though only a third of the surveyed students (n = 22) responded that they had moments of restlessness or anxiety due to the increased frequency of notifications or due to exposure to social media, we cannot say that the rest (n = 41, % = 65.08) are not affected; there is a high probability that the effects appear momentarily in an unconscious or subconscious form, often due to the overlapping of various stress factors (including “background stressor”) or due to the brain’s adaptation to a constant degree of stress. This assumption is consistent with previous findings [15,29,31].

Most students responded that they had not yet noticed any health problems due to excessive smartphone use (n = 41, % = 65.08), and the remaining almost 35% responded that they had experienced eye fatigue (n = 14, % = 22.22), muscle and joint pain (n = 6, % = 9.53), insomnia (n = 5, % = 7.94), and neck/back pain (n = 1, % = 1.59). During the face-to-face dialog at the time of the questionnaire, several students mentioned that they had experienced hearing problems (hearing loss, tinnitus, otitis) because their smartphone is often/permanently connected to headphones (in-ear, with high volume). Multiple studies of the literature in the field have linked excessive smartphone use to the occurrence of health problems, and in some cases to the occurrence of somatic symptoms [30,36,38,39].

Regarding the impact of smartphone use on interpersonal relationships, almost 44.5% of the students who participated in our study (n = 28) responded that it had happened to them at least once that family and friends reproached them for spending too much time on their smartphones, but even more worryingly, the same share of students (n = 28, % = 44.44) said that they had happened to consider spending time on their smartphones more enjoyable than in the company of family and friends. Here the implications are both social and psychological in nature. We could conclude that the students who participated in our study prefer to spend time on their smartphones to the detriment of their family due to the comfort offered by the smartphone (control over it, entertainment, release), digital simulation (face-to-face relationships are slower, less interactive), avoidance of reality and social pressure (various expectations from friends and family), and, last but not least, due to the loss of the ability to communicate face-to-face (students have become more anxious in direct, interpersonal relationships). Our findings are consistent with the findings of the literature in the field, which has shown that problematic, excessive smartphone use among students affects interpersonal relationships [29,31,32], leading to isolation and alienation from family and friends [40,41].

4. Conclusions

Problematic smartphone use among university students negatively influences all dimensions of sustainable education—cognitive, socio-emotional, and behavioral. It undermines responsible consumption, the development of empathy and social responsibility, and the practice of sustainable behaviors. Such compulsive or sometimes addictive digital habits pose risks not only to the achievement of sustainable education goals but also to students’ physical, mental, and emotional health. Overall, both sustainable education and student well-being are compromised by the patterns of smartphone use developed in daily life. The detailed investigation of this issue, through bibliometric analysis as well as observational research, provides a comprehensive perspective that allows for the examination of large volumes of scientific literature, facilitates the identification of diverse research contributions, and contributes to a deep understanding of this multidimensional topic. Such analysis is essential in academic research, as it allows for the assessment of scientific impact and the anticipation of emerging trends and future research directions. The findings can inform other researchers and research institutions, and funding bodies, and serve as a basis for academic and policy decision-making. Moreover, the combination of bibliometric investigation with a cross-sectional study offers critical insights into the influence of problematic smartphone use on sustainability in education and student well-being.

4.1. Research Contributions

This study combined a bibliometric analysis, in the first part, with a cross-sectional study, in the second part, to allow for the outline of a general picture of the issues regarding smartphone use among students, especially in the current digital era, in which the role of tools specific to the industrial revolution (be they smart, portable devices, such as smartphones or software, IT platforms, digital networks, automation, etc.) is undeniable as a link in interconnectivity, which contributes to a faster and smarter world, but also involves important challenges, such as the increase in problematic use of these tools, the emergence of addictive behaviors, and the need to adapt education, business models, and social behaviors to new realities.

For the bibliometric investigation, we carried out a rigorous selection of the works, which involved several inclusion/exclusion filters, followed by a double check of the documents and, finally, an intellectual network of 593 documents obtained from the Web of Science Core Collection database was formed, and for the creation of visual maps in the bibliometric analysis we used VOSviewer software, version 1.6.20. As a trend of the publications, it was found that the issues addressed are closely correlated with the trends of mobile technology and with the evolution of services that can be performed using a mobile phone. Thus, in the early period up to 2015, the authors discovered the excessive use of text messages among students; addictive behaviors towards the internet, games, online shopping; correlations with psychological factors and anxious, depressive behaviors, with a decrease in the quality of life; correlations between the decrease in academic performance and the excessive use of the smartphone; and gradually, addiction scales are being validated at a national level, in order to measure the degree of addiction, especially in the context of observing new behaviors related to phone addiction (such as phubbing). Between 2016 and 2025, interest in the issue began to grow, with almost 96.8% of the total publications analyzed having appeared now. The authors note that students with psychosocial problems are vulnerable to excessive use of cyber-technological devices; more and more versions of the national technology addiction scales are being validated, and based on them, the evidence that smartphone addiction leads to decreased academic performance, quality of life, and increased stress is evident. In the literature in the field, terms such as “cyberloafing”, “nomophobia”, “cyberbullying”, “fear of missing out”, and “bedtime procrastination” are gaining notoriety.

A diversification of the academic landscape is noted in the period 2016–2025, when the growth is impressive among authors, countries, and publishers. Regarding productivity metrics, a positive trend in collaboration between authors is observed (the average authors/article has increased), and the authors/countries ratio has increased by over six times. Young people and students are the age group most vulnerable to the negative effects of using technology and digital devices because they are the most active users. Therefore, researchers were interested in obtaining information on the excessive exposure of young people to mobile technology, the impact on academic performance, physical and mental health, and social relationships, and to offer solutions for a balanced use of digital devices, as well as prevention/awareness measures.

The main research directions, the categories of subjects at risk of addiction, and the trends in the field can be captured through the bibliometric analysis of the most cited works. “Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students” has 817 citations according to WOS and pointed to a correlation between daytime dysfunctions, sleep quality, anxiety, depression, and the degree of smartphone use [30]. “Relationships among smartphone addiction, stress, academic performance, and satisfaction with life” has 697 citations according to WOS and analyzed the bi-directional relationship between smartphone addiction and quality of life, stress, and academic performance [32]. These first two examples show us interdisciplinarity in approach, because the complexity of the researched topic implies a multidisciplinary treatment for the full understanding of the impact and implications of this harmful behavior for students.

Regarding the visualization of the publication network by country, most publications were identified as having China as their country of origin, which is known for treating the issue of digital addiction as a public health issue, with various regulations to ensure appropriate content and proposals for reducing time spent online. Turkey is the second country of origin of publications in the field, and the data shows that 49.1% of the population using a smartphone are in the student age group (18–24 years). Other countries of origin of publications are England and the United States of America. The co-authorship by country analysis establishes that the country with the highest total link strength is England (TLS = 93) with a total of 49 documents and collaborations with 33 countries; England’s connections are the strongest, as a weighted sum of collaborations. China follows, with a TLS = 89 and collaborations with 22 countries for a total of 145 documents, and then the USA with a TLS = 67 and collaborations with 34 countries for a total of 45 documents. The most representative author is Griffiths Mark D. with 26 publications, 1501 citations and the highest total link strength, equal to 78. Lin, Chung-Ying has a total of 10 documents, 701 citations, 15 links, and a total link strength equal to 48. The two are in proximity to the nodes in the bibliometric map created because they have common interests in terms of the research topics addressed. The term with the most occurrences is “smartphone addiction”, with a total of 212 occurrences, indicating the excessive, but sometimes incorrect use of the mobile phone. Other keywords in co-occurrence analysis were “addiction”, “mobile phone addiction”, “problematic smartphone use”, “problematic internet use”, “self-control”, “social media addiction”, “academic-performance”, “prevalence”, “predictors”, “anxiety”, “depression”, “sleep quality”, “stress”, “nomophobia”, “loneliness”, etc. Keywords included in the clustering map were grouped into four clusters, which targeted the influence of problematic smartphone use on academic performance, health, addiction, and on psychological distress.

The bibliometric analysis highlighted the fact that only four works originate from Romania [51,52,53,54], and because we wanted to capture the issue addressed among Romanian students as well, we used a questionnaire as a quantitative research tool (20 questions structured in 5 sections), which was distributed to a total of 65 students from the Economics and International Affairs bachelor’s degree specialization, years 2 and 3 (63 questionnaires being validated). The surveyed students have a high and very high level of average daily smartphone use, more precisely 71.43% of respondents stated that they spend on average between 4 and 7 h per day, and 17.46% of students even over 7 h per day. Smartphone behavior has become compulsive, with 80.95% of the surveyed students reporting checking their smartphones several times an hour, which can lead to loss of attention, decreased productivity, and a negative impact on learning. Academic preparation ranks last in the activities of the students in our sample on smartphones, and while most surveyed students do not consider that smartphone use influences their learning and academic performance, there is also a share of almost 29% of those surveyed who consider that smartphone use distracts them from learning and prevents them from completing their duties on time. Thus, the problem of smartphone use in the educational context is noted, especially since over 71% of respondents said that they lose concentration or postpone homework because of their smartphones and all of them stated that they lose attention in class to a certain extent because of smartphone use. Another compulsive behavior is demonstrated by the fact that although the surveyed students responded that they do not feel agitated or nervous if they do not have access to their smartphones, most of them cannot control the time spent on their smartphones and feel the need to reduce the time spent on their smartphones. A third of the respondents perceive a connection between the level of stress and the time spent on the smartphone. The causes are multiple: overstimulation due to multitasking, inability to mentally disconnect, insomnia due to intensive smartphone use, anxiety due to exposure to social media, etc. Another third stated that health problems arose due to excessive smartphone use (eye fatigue, muscle/joint pain, insomnia, neck/back pain). The interpersonal relationships of the students in our sample suffered due to excessive smartphone use. Almost half of the respondents said that they are reproached for spending too much time on smartphones, but despite this they consider spending time on the smartphone more pleasant than in the company of family and friends. Thus, smartphone use is also problematic among the surveyed students, like the international trend highlighted by the bibliometric analysis carried out in this study. Although the respondents’ answers point more to the existence of compulsive behavior that suggests a self-control conflict at the expense of addictive behavior, it is possible that the students are not aware of the problematic use of the smartphone in their lives, especially since it has become a “habit”, a “social norm” nowadays. But their answers indicate the existence of some risks and problems, which can degenerate if not addressed properly. We note that the data obtained from the cross-sectional study provide a first, preliminary picture of the issue of smartphone use among Romanian students, given that the initial bibliometric analysis showed an obvious lack of data. By conducting a cross-sectional study, even on a relatively small sample, we were able to offer a local perspective on the situation, which clearly contributes to the attempt to understand the phenomenon. Once again, we are obliged to recommend caution in interpreting the observed results due to the relatively small size of the sample that came from a single university, and future studies must be more extensive and diversified.

4.2. Research Limitations

This study has several limitations. First, because the selection of literature in the field was limited to only one scientific database, Web of Science (WOS), its limited, controlled coverage of the literature may lead to the omission of relevant articles published in other sources. Although WOS is an important and rigorous database, considering others (Scopus, Google Scholar) may provide more generous collections of works and numerous analysis tools that lead to a complete literature search.

Another limitation is related to the accuracy of the data (duplicates, citation errors). Even though after performing the advanced search query we performed a manual double check of the generated works so that the titles, abstracts, author keywords, and keywords plus were relevant to the research topic, and the works incorrectly classified as articles were eliminated, the verification process was limited, depending on the availability of access to the respective articles, but also on its vulnerable, human-dependent nature, which can lead to involuntary omissions, subjective interpretations, and influence on the accuracy of the data and their validation.

A third limitation is related to geographical bias. The fact that there is unequal access to resources among researchers, that English is preferred by specialized journals and international databases, or that editorial standards present a great diversity across countries and regions can lead to disparities in research; in some situations, it is an underrepresentation of research due to limited access.

The fourth limitation, as mentioned in the previous section, consists of the relatively small sample (n = 63), drawn from a single specialization within one faculty. Certainly, such a limited sample reduces the possibility of generalizing the findings to the broader student population in Romania and requires caution in interpreting the data, since they may not accurately reflect characteristics of all Romanian students. The generalization of the results can be obtained by including a larger number and more diverse samples of students from multiple faculties or universities.

4.3. Recommendations for Administrators and Policymakers

The results obtained from the research can serve to substantiate campaigns and policies at institutional and national levels, which will contribute to the adoption of effective measures aimed at reducing the negative impact of problematic, excessive smartphone use among university students. In this regard, based on the experiences and findings from bibliometric analysis, but also from the cross-sectional study, several recommendations for administrators and policymakers can be highlighted:

• Integrating digital education programs (courses, seminars, workshops) into the higher education curriculum. Digital education can reinforce the significant role of digital technology in the educational process but also signal the risks of excessive use. In this way, students can learn how important digital self-control is, promoting responsible use.
• Adopting firm rules regarding smartphone use during classes. In this way, it increases students’ academic engagement by improving attention and concentration.
• Provide counseling services for students exhibiting compulsive smartphone behaviors or digital/smartphone addiction.
• Create “Mindfulness Zones” or “Tech-Free Zones” as spaces where the use of digital devices is restricted and where students can take a break from digital stimuli or distractions and can recreate through pleasant activities (reading, meditation, drawing, etc.) or conversations with colleagues.
• Promote awareness campaigns on the risks of excessive smartphone use. These campaigns should be organized not only within universities, but also at local and national levels and should involve educators, psychologists, sociologists, technology and information specialists, health professionals (neurologists, orthopedists, ophthalmologists), local authorities, and stakeholders from civil society.
• Fund research on the impact of excessive use of technologies, including the development of tools to assess and monitor digital addiction and its effects.

4.4. Directions for Future Research

Considering the complexity and multidisciplinary nature of the topic of problematic smartphone use among students, as well as the findings obtained through this study, future research becomes necessary to understand this phenomenon.

The following research questions are proposed, derived from the conclusions of this paper:

• Are there significant differences in problematic smartphone use among students based on sexes or field of study?
• Are there significant differences in smartphone usage patterns between different educational levels (bachelor’s, master’s, doctoral)?
• How do smartphone usage patterns among students influence academic performance?
• How much do firm rules on smartphone use during class contribute to increasing students’ attention and concentration?
• What measures can be adopted to reduce the risks involved in problematic, excessive smartphone use among students?
• In what ways does problematic smartphone use affect students’ communication skills and social responsibilities?
• What types of personality or emotional experiences of students increase vulnerability to smartphone addiction?
• What is the relationship between excessive consumption of digital technologies and sustainable behavior of students?
• To what extent do recreational spaces for students (Mindfulness Zones, Tech-Free Zones) contribute to responsible, healthier digital consumption?

From a methodological point of view, in order to obtain more rigorous, complex, and robust research in the future, the following should be considered: expanding and diversifying the sample for cross-sectional studies, to ensure greater representativeness; using a mixed research methodology, combining quantitative and qualitative methods; conducting comparative analyses between different groups of subjects, to ensure an in-depth interpretation of the issue; conducting longitudinal studies; interdisciplinary research teams; integrating digital tools into research; and the use of additional scientific databases besides WOS (such as Scopus, Google Scholar), as well as other tools and software beyond VOSviewer (such as CitNetExplorer, Bibliometrix, Publish).